Naming Contest: A New “A”-Word For A.I.

Here’s a naming contest: pick a new word the letter “A” stands for in A.I. – conventionally known as artificial intelligence. What would be your pick?

Candidate #1: A = Amplified

Just like A.I., machine learning is an amplifier of all things human…reflecting [human actions] exponentially back into society, that’s where the hidden danger really is.

Dekai Wu, Professor at the Hong Kong University of Science & Technology, one of eight inaugural members of Google’s AI Ethics Council, in an interview on the “Exponential View with Azeem Azhar” podcast

Think of A.I. as a 10-X magical amplifier. Whatever we feed it – whether good or bad – will get reflected back at us with greater force.

One problem this brings is to amplify our biases – whether they are explicit or implicit. For instance, machines could internalize stereotypes, as a study found this: “European American names were more closely associated with pleasant words than they were with unpleasant ones, in comparison to African American names, and female names were more closely associated with words that have familial connotations than with career-oriented words, as compared to male names.”

Candidate #2: B = Biased?

Being original, you come up with this out-of-the-box answer: why don’t we scrap the letter “A” altogether, and replace it with the letter “B” instead? How about B.I. for “Biased Intelligence”?

While “artificial” is a relatively neutral term, “amplified” is neutral / slightly positive, “biased” takes a U-turn and takes on a negative connotation. But the picture is not all gloomy. On the bright side, biases from algorithms may be easier to spot:

In contrast to human thought processes, certain elements of algorithmic decision-making—such as the inputs used to make predictions and the outcomes algorithms are designed to estimate—are inherently explicit, though not always publicly visible.

Amy Merrick, “How making algorithms transparent can promote equity“, Chicago Booth Review

Biases from algorithmic decision-making are more explicit (than human biases), in that we could identify & measure them with objective data. We could analyze the record of all decisions made. In contrast, it is much harder to quantify how “biased” an actual person is in real life – it’s hard to imagine tracking every single decision, action or word said by a person and analyzing how much of that is attributable to “bias”.

Candidate #3: Get Rid of the 1st Letter Altogether

Now to be even more original, some of you may question why we need an adjective in front of the word “intelligence” in the first place. As mentioned in this Chinese interview on the podcast “迟早更新”, a guest speaker mentioned the ultimate purpose of artificial intelligence is to get rid of the “A” – i.e., the intelligence of machines no longer seems artificial.

You could argue if we want our name to be more aspiring and reflect our optimism about the future, we should adhere to “less is more” and scrap the letter “A” in the first place.

Candidate #4 (&5): Let’s Go Natural & Organic

At this point, some of you may ask: since the opposite of “artificial” is “natural”, why don’t we rename A.I. as Natural Intelligence? Or if we want to stick with the initials (since people are already so used to it), we could call it All-Natural Intelligence? Or perhaps Almost-Natural Intelligence for now, before A.I. hits perfection?

Or how about replacing “natural” with its cousin, “organic”? Say Almost-Organic Intelligence? Or Inorganic Intelligence for a fancy twin-initial of I.I.?

I will leave it to yourself to explore the rabbit hole…be sure not to dig too deep! 🙂

What is your pick or nomination? Share your views – write to me at or reach me on LinkedIn.

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